All related (5)
Savita Kini
Director of Product Management, Speech and Video AI, CiscoMarch 2

This is not a simple question. There is no such thing as a "traditional PM" because PM roles and responsibilities differ by industry segment. There are substantial differences in PM roles from consumer app to enterprise app to hardware and enterprise infrastructure. 

Fundamentally the role of the PM is still the same - to consider customer problems, potential solution approaches, and lead them from concept to launch and facilitate a continous innovation lifecycle. The only difference here in AI/ML PM is a new approch to solving the problem with AI/ML tools and frameworks. So anyone with a "Learning mindset", ability to pick up on the AI/ML technologies and comfortable in ambiguity as this field is still growing, -- would do very well. 

Suhas Manangi
Group Product Manager, AirbnbJune 6

5 years from now, likely there is going to be no difference between a Traditional PM and AI PM. AI is going to be used/present in all products. I see "Traditional PM role" as a foundational one to have, upon which one can grow to become a good AI PM. Good Traditional PM with aptitude for tech and data science is likely to do well as a good AI PM. Taking a Udemy course on basics of AI/ML, and applying to every day PM job will be a great start.

Savita Kini
Director of Product Management, Speech and Video AI, Cisco
Key traits for AI PM is no different from other PM roles -- empathy for customer issues, ability craft / create / articulate problems and how we might approach the solution, industry and domain experience, and collaborative leadership to work with engineering. Willingness to learn or prior experience or understanding of AI/ML modeling challenges, and how they can be use in the context the industry / domain where it is applied is ofcourse a big plus. 
Suhas Manangi
Group Product Manager, Airbnb
Being a good PM helps becoming a good manager of PMs, but is not a sufficient condition. I have seen below 3 as top challenges/opportunities unique to GPMs: 1. Deligating, and trusting your direct report PMs to care about Customers as much as you do, if not more. 2. Providing saftey net for PMs to fail fast, learn, and iterate, but as well the essential framework on lowering the cost of failure to ensure contribution to business impact. 3. Knowing that PM skills are not hard to aquire, but takes time. Coaching the team on specific PM skills need persistence and patience....
Deepak Mukunthu
Senior Director of Product, AI/ML Platform, DocuSign
I have seen 4 different types of AI Product Managers: 1. Product focused: Infuse intelligence into products (e.g., search, personalization) 2. Platform focused: Infrastructure & tooling for data scientists and ML engineers to manager ML lifecycle 3. Business/Operations focused: ML to improve product adoption/operations (e.g., customer churn prediction) or business outcomes (e.g., revenue forecasting). This role typically works with data science teams that work on internal optimizations leveraging ML. 4. Research focused: Bringing AI research breakthroughs to market If you are interes...